M. Bonfanti

Towards Reduced Order Models via Robust Proper Orthogonal Decomposition to Capture Personalised Aortic Haemodynamics

This paper uses reduced order models and proper orthogonal decomposition to capture personalized aortic hemodynamics from in vitro data, showing that few modes can represent flow features accurately.

RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity

The paper identifies RAGE as a novel receptor for SARS-CoV-2 that mediates monocyte infection and contributes to COVID-19 severity through single-cell analysis of immune responses.

A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

This paper introduces an MRI-based data fusion method for simulating aortic haemodynamics, achieving accurate and efficient patient-specific compliant simulations without CT data.

Effective Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations with In Vivo and In Vitro Validation

This paper develops a computational framework to simulate AVM haemodynamics and predict embolisation outcomes, validated with clinical and experimental data.

Patient-specific haemodynamic simulations of complex aortic dissections informed by commonly available clinical datasets

This study uses patient-specific CFD models with clinical data to analyze haemodynamics in Type-B aortic dissections, revealing insights into disease state and risk factors.